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Improving Traceability Link Recovery Using Fine-grained Requirements-to-Code Relations

Hey, Tobias ORCID iD icon; Chen, Fei; Weigelt, Sebastian; Tichy, Walter F. ORCID iD icon

Abstract (englisch):

Traceability information is a fundamental prerequisite for many essential software maintenance and evolution tasks, such as change impact and software reusability analyses. However, manually generating traceability information is costly and error-prone. Therefore, researchers have developed automated approaches that utilize textual similarities between artifacts to establish trace links. These approaches tend to achieve low precision at reasonable recall levels, as they are not able to bridge the semantic gap between high-level natural language requirements and code. We propose to overcome this limitation by leveraging fine-grained, method and sentence level, similarities between the artifacts for traceability link recovery. Our approach uses word embeddings and a Word Mover's Distance-based similarity to bridge the semantic gap. The fine-grained similarities are aggregated according to the artifacts structure and participate in a majority vote to retrieve coarse-grained, requirement-to-class, trace links. In a comprehensive empirical evaluation, we show that our approach is able to outperform state-of-the-art unsupervised traceability link recovery approaches. ... mehr


Postprint §
DOI: 10.5445/IR/1000140404
Veröffentlicht am 29.11.2021
Originalveröffentlichung
DOI: 10.1109/ICSME52107.2021.00008
Scopus
Zitationen: 7
Dimensions
Zitationen: 8
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator ISBN: 978-1-66542-882-8
KITopen-ID: 1000140404
Erschienen in 37th IEEE International Conference on Software Maintenance and Evolution (ICSME), 27.9.-01.10.2021 Luxemburg
Veranstaltung 37th IEEE International Conference on Software Maintenance and Evolution (ICSME 2021), Stadt Luxemburg, Luxemburg, 27.09.2021 – 01.10.2021
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 12–22
Vorab online veröffentlicht am 24.11.2021
Schlagwörter Traceability, Traceability Link Recovery, Requirements Engineering, Word Embeddings, Natural Language Processing, Word Movers Distance
Nachgewiesen in Dimensions
Scopus
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